Real-World Utilization of Biomarker Testing for Patients with Advanced Non-Small Cell Lung Cancer in a Tertiary Referral Center and Referring Hospitals

MOMENT registry: Patients with advanced non-small-cell lung cancer harboring MET exon 14 skipping treated with systemic therapy

Aim: MET exon 14 (METex14) skipping occurs in 3-4% of non-small-cell lung cancer (NSCLC) cases. Low frequency of this alteration necessitated open-label, single-arm trials to investigate MET inhibitors. Since broad MET biomarker testing was only recently introduced in many countries, there is a lack of historical real-world data from patients with METex14 skipping NSCLC receiving conventional therapies. Given the rarity of this population and limitations of existing real-world data sources, the MOMENT registry aims to prospectively collect uniform, comprehensive, high-quality data from patients with METex14 skipping advanced NSCLC treated in routine clinical practice, which can support clinical and regulatory decision making. Patients & methods: MOMENT is a multinational, non-interventional disease registry collecting data on patients with METex14 skipping advanced NSCLC receiving any systemic anticancer therapy. Newly diagnosed patients and those already receiving treatment are eligible. Patients with previous participation in a clinical trial can be included if they receive at least one subsequent therapy line in a routine clinical setting. Eligible systemic treatment includes all available anticancer therapies (approved, conditionally approved or provided through Early Access). Data collection includes biomarker testing results, demographics, baseline clinical characteristics, treatment details and effectiveness, safety information and imaging. Registry site inclusion is dependent on confirmation that local METex14 skipping detection methods are sufficient to confirm METex14 skipping status. MOMENT is currently active at more than 60 sites across Europe and North America and approximately 700 patients are expected to be enrolled within the next 4 years. The first patient was enrolled on 4 October 2022. After completion of data collection, MOMENT data can be shared with external parties to conduct non-interventional studies. Discussion/conclusion: The MOMENT registry collects comprehensive, high-quality real-world data from patients with METex14 skipping advanced NSCLC receiving systemic anticancer treatment in a routine clinical setting, to enable future studies informing regulatory decisions and optimal care for this rare population. Clinical Trial Registration: NCT05376891 (ClinicalTrials.gov); EUPAS47602 (EU PAS register no.).

Relevant factors for policy concerning comprehensive genomic profiling in oncology: stakeholder perspectives

BACKGROUND

Comprehensive genomic profiling (CGP) can identify targets beyond standard of care, potentially revolutionizing personalized cancer management. However, conducting well designed studies in this rapidly evolving field is complex and demands time and investments. Consequently, the total added value of CGP remains uncertain. Clinical benefit and costs often are driving factors in coverage decisions. Recently, five additional factors were identified in the literature that can influence the choice for targeted profiling vs. CGP, specifically: "feasibility", "test journey patient/physician", "wider implications of diagnostic results", "organization of laboratories", and "scientific spillover". The objective of the current study is to examine the role and importance assigned to these five additional factors for a comprehensive technology assessment by different stakeholders.

METHODS

Purposive sampling was used to identify respondents from 4 stakeholder groups (i.e., medical specialists, molecular specialists, patient representatives, and policymakers) from different regions and hospital types (academic vs. non-academic) in the Netherlands. In semi-structured interviews, respondents scored the importance to decision-making of the five factors on a 0 (not important) to 5 (essential) scale. Reasoning behind the scores were elicited using open-ended follow-up questions. Transcripts were independently double-coded by two researchers using thematic analysis.

RESULTS

Nineteen stakeholders (100% response rate; medical specialists (n = 7), molecular specialists (n = 7), patient representatives (n = 2), and policymakers (n = 3)) were interviewed. We observed differences between stakeholders in the relative importance assigned to the factors (range of median importance scores: 2-5). Overall, "wider implications of diagnostic results", primarily CGP's potential to identify additional treatment options, was deemed the most important factor alongside clinical benefit and costs in decision-making about CGP (median range: 3-5). While the "organization of laboratories" was considered less important (median range: 3-4), opposing arguments and preferences regarding the organization of laboratories were identified, with participants from academic centers preferring a centralized approach whilst non-academics preferred a decentralized approach.

CONCLUSIONS

Stakeholders deemed "wider implications of diagnostic results", "feasibility", and "test journey" the most important considerations for decision-making about targeted profiling vs. CGP alongside clinical benefit and costs. For policy decision-making, it is important to understand the arguments behind the heterogeneous opinions, often related to the setting they originate from.

Factors for a broad technology assessment of comprehensive genomic profiling in advanced cancer, a systematic review

Comprehensive Genomic Profiling (CGP) allows for the identification of many targets. Reimbursement decision-making is, however, challenging because besides the health benefits of on-label treatments and costs, other factors related to diagnostic and treatment pathways may also play a role. The aim of this study was to identify which other factors are relevant for the technology assessment of CGP and to summarize the available evidence for these factors. After a scoping search and two expert sessions, five factors were identified: feasibility, test journey, wider implications of diagnostic results, organisation of laboratories, and "scientific spillover". Subsequently, a systematic search identified 83 studies collecting mainly evidence for the factors "test journey" and "wider implications of diagnostic results". Its nature was, however, of limited value for decision-making. We recommend the use of comparative strategies, uniformity in outcome definitions, and the inclusion of a comprehensive set of factors in future evidence generation.

Assessing the Cost-Effectiveness of Next-Generation Sequencing as a Biomarker Testing Approach in Oncology and Policy Implications: A Literature Review

OBJECTIVE

A key hurdle in broader next-generation sequencing (NGS) biomarker testing access in oncology is the ongoing debate on NGS's cost-effectiveness. We conducted a systematic review of existing evidence of the costs of NGS as a biomarker testing strategy in oncology and developed policy suggestions.

METHODS

We searched multiple databases for studies reporting cost comparisons and cost-effectiveness of NGS across oncology indications and geographies between 2017 and 2022, inclusive. Inclusion criteria were established based on indication and type of cost-effectiveness analysis provided. We validated analyses and policy recommendations with 5 payer/policy maker interviews in the United States, Europe, and United Kingdom.

RESULTS

Of the 634 identified studies, 29 met inclusion criteria, spanning 12 countries and 6 indications. Cost comparisons of NGS were evaluated using 3 methodologies: (1) comparison of direct testing costs, (2) comparison of holistic testing costs, and (3) comparison of long-term patient outcomes and costs. Targeted panel testing (2-52 genes) was considered cost-effective when 4+ genes were assessed, and larger panels (hundreds of genes) were generally not cost-effective. Holistic analysis demonstrated that NGS reduces turnaround time, healthcare staff requirements, number of hospital visits, and hospital costs. Finally, studies evaluating NGS testing including the cost of targeted therapies generally found the incremental cost-effectiveness ratio to be above common thresholds but highlighted valuable patient benefits.

CONCLUSIONS

Current literature supports NGS's cost-effectiveness as an oncology biomarker testing strategy under specific conditions. These findings underscore the need to develop policies to support holistic assessment of NGS to ensure appropriate reimbursement and access.

Non-Small Cell Lung Cancer Testing on Reference Specimens: An Italian Multicenter Experience

INTRODUCTION

Biomarker testing is mandatory for the clinical management of patients with advanced non-small cell lung cancer (NSCLC). Myriads of technical platforms are now available for biomarker analysis with differences in terms of multiplexing capability, analytical sensitivity, and turnaround time (TAT). We evaluated the technical performance of the diagnostic workflows of 24 representative Italian institutions performing molecular tests on a series of artificial reference specimens built to mimic routine diagnostic samples.

METHODS

Sample sets of eight slides from cell blocks of artificial reference specimens harboring exon 19 EGFR (epidermal growth factor receptor) p.E746_AT50del, exon 2 KRAS (Kirsten rat sarcoma viral oncogene homologue) p.G12C, ROS1 (c-ros oncogene 1)-unknown gene fusion, and MET (MET proto-oncogene, receptor tyrosine kinase) Δ exon 14 skipping were distributed to each participating institution. Two independent cell block specimens were validated by the University of Naples Federico II before shipment. Methodological and molecular data from reference specimens were annotated.

RESULTS

Overall, a median DNA concentration of 3.3 ng/µL (range 0.1-10.0 ng/µL) and 13.4 ng/µL (range 2.0-45.8 ng/µL) were obtained with automated and manual technical procedures, respectively. RNA concentrations of 5.7 ng/µL (range 0.2-11.9 ng/µL) and 9.3 ng/µL (range 0.5-18.0 ng/µL) were also detected. KRAS exon 2 p.G12C, EGFR exon 19 p.E736_A750del hotspot mutations, and ROS1 aberrant transcripts were identified in all tested cases, whereas 15 out of 16 (93.7%) centers detected MET exon 14 skipping mutation.

CONCLUSIONS

Optimized technical workflows are crucial in the decision-making strategy of patients with NSCLC. Artificial reference specimens enable optimization of diagnostic workflows for predictive molecular analysis in routine clinical practice.

System dynamics simulation for evaluating implementation strategies of genomic sequencing: tutorial and conceptual model

INTRODUCTION

Precision Medicine (PM), especially in oncology, involve diagnostic and complex treatment pathways that are based on genomic features. To conduct evaluation and decision analysis for PM, advanced modeling techniques are needed due to its complexity. Although System Dynamics (SD) has strong modeling power, it has not been widely used in PM and individualized treatment.

AREAS COVERED

We explained SD tools using examples in cancer context and the rationale behind using SD for genomic testing and personalized oncology. We compared SD with other Dynamic Simulation Modelling (DSM) methods and listed SD's advantages. We developed a conceptual model using Causal Loop Diagram (CLD) for strategic decision-making in Whole Genome Sequencing (WGS) implementation.

EXPERT OPINION

The paper demonstrates that SD is well-suited for health policy evaluation challenges and has useful tools for modeling precision oncology and genomic testing. SD's system-oriented modeling captures dynamic and complex interactions within systems using feedback loops. SD models are simple to implement, utilize less data and computational resources, and conduct both exploratory and explanatory analyses over time. If the targeted system has complex interactions and many components, deals with lack of data, and requires interpretability and clinicians' input, SD offers attractive advantages for modeling and evaluating scenarios.

Real-World Biomarker Test Utilization and Subsequent Treatment in Patients with Early-Stage Non-small Cell Lung Cancer in the United States, 2011-2021

INTRODUCTION

Biomarker testing is increasingly crucial for patients with early-stage non-small cell lung cancer (eNSCLC). We explored biomarker test utilization and subsequent treatment in eNSCLC patients in the real-world setting.

METHODS

Using COTA's oncology database, this retrospective observational study included adult patients ≥ 18 years old diagnosed with eNSCLC (disease stage 0-IIIA) between January 1, 2011 and December 31, 2021. Date of first eNSCLC diagnosis was the study index date. We reported testing rates by index year for patients who received any biomarker test within 6 months of eNSCLC diagnosis and by each molecular marker. We also evaluated treatments received among patients receiving the five most common biomarker tests.

RESULTS

Among the 1031 eNSCLC patients included in the analysis, 764 (74.1%) received ≥ 1 biomarker test within 6 months of eNSCLC diagnosis. Overall, epidermal growth factor receptor (EGFR; 64%), anaplastic lymphoma kinase (ALK; 60%), programmed death receptor ligand 1 (PD-L1; 48%), ROS proto-oncogene 1 (ROS1; 46%), B-Raf proto-oncogene (40%), mesenchymal epithelial transition factor receptor (35%), Kirsten rat sarcoma viral oncogene (29%), RET proto-oncogene (22%), human epidermal growth factor receptor 2 (21%), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (20%) were the 10 most frequently tested biomarkers. The proportion of patients undergoing biomarker testing rose from 55.3% in 2011 to 88.1% in 2021. The most common testing methods were Sanger sequencing for EGFR (244, 37%), FISH (fluorescence in situ hybridization) for ALK (464, 75%) and ROS1 (357, 76%), immunohistochemical assay for PD-L1 (450, 90%), and next-generation sequencing testing for other biomarkers. Almost all the 763 patients who received the five most common biomarker tests had a test before the initiation of a systemic treatment.

CONCLUSION

This study suggests a high biomarker testing rate among patients with eNSCLC in the US, with testing rates for various biomarkers increasing over the past decade, indicating a continuous trend towards the personalization of treatment decisions.

Targeted molecular profiling of solid tumours-Indian tertiary cancer centre experience

PURPOSE

Molecular Profiling of solid tumours is extensively used for prognostic, theranostic, and risk prediction. Next generation sequencing (NGS) has emerged as powerful method for molecular profiling. The present study was performed to identify molecular alterations present in solid tumours in Indian tertiary cancer centre.

METHODS

Study included 1140 formalin Fixed paraffin embedded samples. NGS was performed using two targeted gene panels viz. Ampliseq Focus panel and Sophia Solid Tumor Plus Solution. Data was analyzed using Illumina's Local Run Manager and SOPHiA DDM software. Variant interpretation and annotations were done as per AMP/ACMG guidelines.

RESULTS

Total 896 cases were subjected to NGS after excluding cases with suboptimal nucleic acid quality/quantity. DNA alterations were detected in 64.9% and RNA fusions in 6.9% cases. Among detected variants, 86.7% were clinically relevant aberrations. Mutation frequency among different solid tumours was 70.8%, 67.4%, 64.4% in non-small cell lung (NSCLC), lung squamous cell carcinomas and head neck tumours respectively. EGFR, KRAS, BRAF, ALK and ROS1were commonly altered in NSCLC. Gastrointestinal tumours showed mutations in 63.6% with predominant alterations in pancreatic (88.2%), GIST (87.5%), colorectal (78.7%), cholangiocarcinoma (52.9%), neuroendocrine (45.5%), gall bladder (36.7%) and gastric adenocarcinomas (16.7%). The key genes affected were KRAS, NRAS, BRAF and PIK3CA. NGS evaluation identified co-occurring alterations in 37.7% cases otherwise missed by conventional assays. Resistance mutations were detected in progressive lung tumours (39.5%) against EGFR TKIs and ALK/ROS inhibitors.

CONCLUSION

This is the largest Indian study on molecular profiling of solid tumours providing extensive information about mutational signatures using NGS.

Highly Selective, Single-Tube Colorimetric Assay for Detection of Multiple Mutations in the Epidermal Growth Factor Receptor Gene

Many closed-tube methods are designed to detect DNA biomarkers. However, the utility of biomarkers such as a DNA mutation related to personalized medicine is limited as the operation of expensive detection instruments requires well-trained technicians. Therefore, we developed a simple and cheap colorimetric assay based on aggregation of silica-gold nanoparticle-modified probes, with linking probes, to detect mutations. This method consists of target amplification, sequence identification, and aggregation of the silica-gold nanoparticle-modified probes. All reactions are controlled by one individual and proceed sequentially, in a single tube, with no manual intervention. Approximately 10 copies of target DNA were detected with this assay, using 12 hot-spot mutations in exon 19 of EGFR gene as the example. In artificial samples, 0.1% mutant DNA can be distinguished from wild-type genomic DNA. The technology was tested on 104 clinical samples, which included 29 samples that were positive for an exon 19 deletion. The data were consistent with amplification refractory mutation system PCR, with the exception of one weakly positive sample, which was confirmed to be positive by digital PCR. The limit of detection of this colorimetric assay was verified to be better than that of amplification refractory mutation system PCR, and it provides a tool to discriminate multiple mutations in EGFR gene in clinical samples.

C-Biomarker.net: A Cytoscape app for the identification of cancer biomarker genes from cores of large biomolecular networks

Although there have been many studies revealing that biomarker genes for early cancer detection can be found in biomolecular networks, no proper tool exists to discover the cancer biomarker genes from various biomolecular networks. Accordingly, we developed a novel Cytoscape app called C-Biomarker.net, which can identify cancer biomarker genes from cores of various biomolecular networks. Derived from recent research, we designed and implemented the software based on parallel algorithms proposed in this study for working on high-performance computing devices. We tested our software on various network sizes and found the suitable size for each running mode on CPU or GPU. Interestingly, using the software for 17 cancer signaling pathways, we found that on average 70.59% of the top three nodes residing at the innermost core of each pathway are biomarker genes of the cancer respectively to the pathway. Similarly, by the software, we also found 100% of the top ten nodes at both cores of Human Gene Regulatory (HGR) network and Human Protein-Protein Interaction (HPPI) network are multi-cancer biomarkers. These case studies are reliable evidence for performance of cancer biomarker prediction function in the software. Through the case studies, we also suggest that true cores of directed complex networks should be identified by the algorithm of R-core rather than K-core as usual. Finally, we compared the prediction result of our software with those of other researchers and confirmed that our prediction method outperforms the other methods. Taken together, C-Biomarker.net is a reliable tool that efficiently detects biomarker nodes from cores of various large biomolecular networks. The software is available at https://github.com/trantd/C-Biomarker.net.

Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care

PURPOSE

The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking.

METHODS

Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation.

RESULTS

We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test.

CONCLUSION

WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer.

Biomarker Testing for Patients With Advanced/Metastatic Nonsquamous NSCLC in the United States of America, 2015 to 2021

Introduction

NSCLC is a solid tumor with a growing number of actionable biomarkers that may inform treatment. Current guidelines recommend a broad, panel-based approach be taken to identify actionable markers. This retrospective study used a deidentified electronic health records database in the United States to evaluate utilization of various testing modalities.

Methods

Data from all adult patients diagnosed with having advanced/metastatic nonsquamous NSCLC between January 2015 and March 2021 were eligible if there was evidence of systemic therapy within 90 days of diagnosis.

Results

Records from a total of 17,513 patients (91.6% from community-based practices) were eligible with 83,064 genomic biomarker tests recorded from 2015 to 2021. The proportion of patients who received biomarker testing by next-generation sequencing (NGS)-based methods ranged from 28.3% in 2015 to 68.1% in 2020. The proportion of biomarker testing methods with inconclusive or unsuccessful results ranged from 3.4% for NGS to 9.7% for fluorescence in situ hybridization. The median time to receive results ranged from 4.0 days for polymerase chain reaction-based tests to 10.0 days for immunohistochemistry- and NGS-based tests. Median time to receive results was 8 days for academic and 9 days for community practices.

Conclusions

These real-world data suggest increased adoption of NGS-based testing, yet nearly one-third of all patients with advanced/metastatic nonsquamous NSCLC still did not receive broad-based genomic testing by 2020.

Development and Validation of a Prognostic Index Based on Genes Participating in Autophagy in Patients With Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a deadly respiratory system malignancy with poor prognosis. Autophagy is essential for the beginning, development, and therapy resistance of cancer. However, the expression of genes participating in autophagy in LUAD and their associations with prognosis remain unclear.

Methods

Predictive genes participating in autophagy in LUAD samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were investigated. TCGA and GEO cohorts were divided into two risk groups, while the low-risk group having a longer overall survival (OS) time. This article aims to point out the interaction between genes participating in autophagy and immune function, immune checkpoints, and m6a in LUAD. The prediction model was designed for exploring least absolute shrinkage and selection operator (LASSO) regression. It has been revealed that gene expression and autophagy are inextricably connected.

Results

Genes participating in autophagy were shown to be somewhat overexpressed in the high-risk group even though no different clinical symptoms were present, indicating that they might be used in a model to predict LUAD prognosis. The majority of genes participating in autophagy prognostic signatures controlled immunological and tumor-related pathways, according to gene set enrichment analysis (GSEA). KRT6A, KYNU, IGFBP1, DKK1, PKP2, PLEK2, GAPDH, FLNC, and NTSR1 might be related to the oncology process for LUAD patients. CERS4, CMAHP, and PLEKHB1 have been identified as being associated with low risk in patients with LUAD. Furthermore, the immune function and m6a gene expression differed significantly between the two groups.

Conclusions

Genes participating in autophagy are connected to the development and progression of LUAD. LUAD patients’ prognoses are often foreseen utilizing matched prognostic models. Genes participating in autophagy in LUAD may be therapeutic targets that ought to be investigated more.

Early Cost Effectiveness of Whole-Genome Sequencing as a Clinical Diagnostic Test for Patients with Inoperable Stage IIIB,C/IV Non-squamous Non-small-Cell Lung Cancer

BACKGROUND

Advanced non-small-cell lung cancer (NSCLC) harbours many genetic aberrations that can be targeted with systemic treatments. Whole-genome sequencing (WGS) can simultaneously detect these (and possibly new) molecular targets. However, the exact added clinical value of WGS is unknown.

OBJECTIVE

The objective of this study was to determine the early cost effectiveness of using WGS in diagnostic strategies compared with currently used molecular diagnostics for patients with inoperable stage IIIB,C/IV non-squamous NSCLC from a Dutch healthcare perspective.

METHODS

A decision tree represented the diagnostic pathway, and a cohort state transition model represented disease progression. Three diagnostic strategies were modelled: standard of care (SoC) alone, WGS as a diagnostic test, and SoC followed by WGS. Treatment effectiveness was based on a systematic review. Probabilistic cost-effectiveness analyses were performed, and threshold analyses (using €80,000 per quality-adjusted life-year [QALY]) was used to explore the early cost effectiveness of WGS.

RESULTS

WGS as a diagnostic test resulted in more QALYs (0.002) and costs (€1534 [incremental net monetary benefit -€1349]), and SoC followed by WGS resulted in fewer QALYs (-0.002) and more costs (€1059 [-€1194]) compared with SoC alone. WGS as a diagnostic test was only cost effective if it was priced at €2000 per patient and identified 2.7% more actionable patients than SoC alone. Treating these additional identified patients with new treatments costing >€4069 per month decreased the probability of cost effectiveness.

CONCLUSIONS

Our analysis suggests that providing WGS as a diagnostic test is cost effective compared with SoC followed by WGS and SoC alone if costs for WGS decrease and additional patients with actionable targets are identified. This cost-effectiveness model can be used to incorporate new findings iteratively and to support ongoing decision making regarding the use of WGS in this rapidly evolving field.

Early technology assessment of using whole genome sequencing in personalized oncology

Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.